Introduction

Telework has evolved steadily since the term “telecommuting” was introduced in 1972—emerging from remote work on NASA communications—with “flexplace” following in 19791. The idea moved from practice to policy with the United States Telework Enhancement Act of 2010, which sought to improve security and efficiency for federal employees1. Together, these milestones established telework as a credible alternative to office-bound work and loosened organizations’ reliance on fixed locations and rigid hours2, leading to entirely different responses and preferences of workers and organizations3.

The COVID-19 pandemic dramatically accelerated telework adoption worldwide, with millions experiencing remote work for the first time and regulatory activity increasing visibly throughout 20204. This transformation from a flexible work option to an organizational necessity revealed both telework’s potential and limitations, with adoption rates remaining significantly higher post-pandemic than pre-2020 levels4,5. In the Gulf Cooperation Council region, telework adoption surged dramatically during COVID-19, with Dubai increasing from 13 to 62%, Abu Dhabi from 18 to 51%, and other emirates from 15 to 56%6.

Research evidence and measurement instruments

Research demonstrates that telework provides employees greater schedule control, improving work-life balance across generational cohorts, with Baby Boomers showing particularly high flexibility preferences7,8. Productivity benefits emerge from personalized work environments, reduced commuting stress, fewer workplace interruptions, and the ability to work during optimal hours9,10,11. Additionally, telework generates significant cost savings for both employees (reduced commuting, work attire, and meals) and organizations (decreased office space, utilities, and operational overhead), with the pandemic highlighting these financial advantages10,12 (Table 1).

Table 1 Description of the most relevant advantages and drawbacks of telework.
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However, telework also presents substantial challenges. Social isolation and reduced colleague interaction represent primary concerns, as teleworkers miss informal conversations and social bonding crucial for workplace relationships and community building9,11,13. Technology dependence creates vulnerability to connectivity issues and workflow disruptions14,15. Communication barriers and misunderstandings can emerge, while professional isolation correlates negatively with job performance and engagement, reducing organizational identification and active team participation9,12,14. Furthermore, work-life boundary blurring often leads to burnout among remote workers7 (Table 1).

These multifaceted advantages and drawbacks indicate the need for organizations to carefully consider the implications of telework for employee well-being, productivity, and job satisfaction16. Standardized scales assessing multiple facets are crucial for understanding and enhancing the telework experience, with instruments developed to improve productivity, reduce negative emotions like stress and fatigue, and promote positive work outcomes17,18. Studies have evaluated telework satisfaction across diverse dimensions, including workload and task nature, work hour organization, focus capabilities, family respect for workspace boundaries, supervisor and colleague support, information technology access, and physical work environment14,18,19,20. Beyond satisfaction measures, research has examined affective organizational commitment, professional isolation, and perceived organizational and supervisor support using single-item measures and Likert-type validated scales21.

Extensive exploration has covered job effectiveness22, well-being20, stress15, self-efficacy23, work-life balance24,25, work-family outcomes26, team performance27, productivity19, and work engagement28. The comprehensive E-Work Life (EWL) scale exemplifies this multifaceted approach, measuring job effectiveness, organizational relationships, well-being, and work-life balance29.

The Lebanese context: unique challenges and opportunities

Specific data on telework adoption in Lebanon remains scarce, highlighting a critical research gap. Lebanon presents a particularly compelling case for telework research due to its convergence of economic, political, sociocultural, and technological challenges. As a developing nation recently reclassified as a medium–low-income country by the World Bank35, Lebanon faces unprecedented economic instability, including currency depreciation exceeding 90% and ongoing political turmoil36. These conditions create a unique environment where telework may serve as both an economic necessity and an organizational adaptation strategy.

The Lebanese legal framework presents additional complexity for telework implementation. While no specific national legislation addresses remote work, existing labor regulations provide foundational support through the Labor Law (Act No. 128 of 1991), which outlines employee rights and employer responsibilities regarding working hours, compensation, and leave provisions that must be incorporated into remote work agreements37. Remote workers remain subject to social security contribution requirements, creating a regulatory foundation that supports but does not explicitly govern telework arrangements37. This legal ambiguity necessitates careful consideration of how telework advantages and disadvantages manifest within Lebanon’s unique regulatory environment.

Furthermore, Lebanon’s cultural context adds another layer of complexity, as collectivistic cultural values emphasizing family and community relationships may interact differently with telework’s individualistic advantages compared to Western contexts. The traditional importance of social connections and hierarchical workplace relationships in Lebanese culture may amplify telework’s social isolation drawbacks while potentially enhancing family-related benefits.

Research gap and rationale

Recent studies also link remote work with employee engagement and organizational culture, underscoring the need for context‑appropriate instruments38,39; despite extensive telework research globally, existing measurement instruments may inadequately capture the complex Lebanese experience. Current validated scales, such as the remote working benefits and disadvantages scale developed in Italy40 and the tele attitude scale from Portugal41, emerge from politically and economically stable contexts that differ substantially from Lebanon’s circumstances. The E-Work Life (EWL) scale, measuring job effectiveness, organizational relationships, well-being, and work-life balance29, provides a comprehensive framework but lacks cultural adaptation for Middle Eastern contexts.

Study objectives

This cross-sectional study among 230 Lebanese workers aims to develop and validate a culturally appropriate scale for assessing telework advantages and drawbacks in the Lebanese context. The research addresses critical gaps by:1 examining how telework perceptions manifest within Lebanon’s unique economic and cultural environment,2 developing measurement tools that capture local telework experiences, and3 providing evidence-based insights for policymakers and organizations implementing remote work arrangements.

The validation of this scale will contribute to scientific understanding of telework’s positive and negative impacts on job satisfaction, productivity, and well-being among Lebanese workers, while informing policy development that considers local labor laws and technological infrastructure limitations.

Materials and methods

Study design and participants

A web-based cross-sectional study was conducted from October 2022 to March 2023 using a self-report questionnaire created on Google Forms and distributed via social media platforms (WhatsApp, Facebook, and Instagram). The sampling method was non-probability snowball sampling. Initial participants (workers recruited online) completed the survey and were then asked to refer others who met the inclusion criteria, thereby expanding access to a broader network of employees. This approach was chosen because the sample was geographically dispersed and teleworkers were difficult to reach. Additionally, leveraging teleworkers’ networks made it more feasible to identify further individuals who met the inclusion criteria. The snowball sampling approach yielded 230 participants, divided into three categories based on employment type: face-to-face, telework, and hybrid. The inclusion criteria were work status, age 20 to 80 years, and internet access. Participation was entirely voluntary and unpaid.

Minimum sample size calculation

According to the literature42, 5–10 observations per item are recommended for scale validation. Applying the lower bound of five observations per item to our instrument, which comprises two subscales, yielded a minimum required sample size of 170 participants. The final sample comprised 230 participants, exceeding this threshold.

Survey tool

The questionnaire was available in Arabic and English, and participants could choose their preferred language. It comprised two sections: (1) demographic and work-related characteristics and (2) scales assessing perceptions of telework, including the study-developed scale with two subscales (perceived advantages and perceived drawbacks) and the E-Work-Life Scale (EWL) for conversion validity.

Translation procedure

For the Arabic version of the new scale, one author prepared the initial forward translation. All other co-authors, fluent in both Arabic and English, independently reviewed the translation for accuracy, clarity, and cultural appropriateness. Discrepancies were resolved by consensus, yielding the final Arabic instrument. A formal back-translation was not performed because the items were newly developed by the research team, drawing on questions from the literature and adapted to the Lebanese context, rather than taken from previously validated tools. The EWL followed a forward–backward translation procedure. After an initial forward translation by a bilingual author, an independent bilingual translator blinded to the original English version performed a back-translation. Comparison of the back-translated and original English versions indicated satisfactory semantic equivalence, requiring only minor wording refinements.

Demographic and work-related variables

The variables collected included age, sex (male vs. female), education level, monthly income, area of residence, marital status (married vs. other), household crowding index, the number of children, professional status (self-employed, temporary worker, freelancer, or employee), and working status (telework, in-person, or hybrid work).

Content validity of the perception of telework practices (PTP) scale

The research team, comprising public health experts with extensive experience in occupational, social, and mental health, conducted a comprehensive literature review to develop the PTP scale. Items for both subscales—Perceived Advantages of Telework (PATS) and Perceived Drawbacks of Telework (PDTS)—were inspired by a study among teleworkers during the COVID-19 pandemic43 and supplemented with items tailored to the Lebanese context. The resulting pool comprised 34 items: 12 advantages and 22 drawbacks.

A six-member expert panel validated the scale using the Delphi technique, achieving > 90% consensus on all items. The panel comprised six members: one professor of epidemiology with expertise in medical epidemiology, clinical pharmacy, academic education, and public health research, and five public health academics familiar with the advantages and disadvantages of telework in Lebanon. The panel reviewed the items for clarity and made specific revisions, such as rewording, to ensure comprehensive coverage of relevant issues.

The final questionnaire was piloted with ten working adults to assess clarity. No issues were identified, so no changes were made; accordingly, pilot responses were included in the final dataset.

All PTP items used a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Higher scores on PATS indicate greater perceived advantages; higher scores on PDTS indicate greater perceived drawbacks. Example PATS items include saving time and commuting costs, flexible hours/autonomy, increased productivity, and improved work-life balance. Example PDTS items include lack of a dedicated workspace, limited privacy, household noise, small workspace, and reduced communication with colleagues.

The E-work life (EWL) scale

Satisfaction with telework was assessed using the E-Work Life (EWL) scale29. This 17-item validated tool measures four domains: productivity, organizational trust, flexibility, and interference with work-life balance. Responses are scored on a 5-point Likert scale ranging from strongly disagree1 to strongly agree5, with an option labeled “not applicable” (0). Higher scores indicate more satisfaction with teleworking. In this study, the scale demonstrated excellent internal consistency, with a Cronbach’s alpha of 0.938.

Data analysis

Statistical analyses were performed using SPSS version 25.0. Descriptive statistics included means and standard deviations for quantitative variables and frequencies and percentages for categorical variables.

Construct validity of the PTP scale and subscales was examined using exploratory factor analysis44. Sampling adequacy was assessed with the Kaiser–Meyer–Olkin statistic and Bartlett’s test of sphericity. Factor retention was guided by eigenvalues > 1 and inspection of the scree plot. Varimax rotation was conducted in the PTP total scale, while a Promax rotation was applied when each scale was analyzed separately due to expected inter-factor correlations45. Items with loadings ≥ 0.40 were retained; no items were removed.

A Confirmatory factor analysis (CFA) was performed on a randomly selected 50% subsample using AMOS to assess the factor structure46. Goodness-of-fit indices included the chi-square to degrees of freedom ratio (χ2/df), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker Lewis Index (TLI). Acceptable fit was defined as χ2/df between 2 and 5, RMSEA < 0.11 (with < 0.05 indicating close fit), and CFI/TLI ≥ 0.90.

Internal consistency was estimated with Cronbach’s alpha for the PTP total scale and each subscale47. Pearson correlations examined the PTP scale, its subscales, and convergent validity with other measures48.

Statistical significance was set at p < 0.05.

Results

Sample description

Table 2 presents sociodemographic and other characteristics of the 230 Lebanese adults in the sample. During the COVID-19 pandemic and economic crisis, 54.8% worked on-site, 20.4% worked exclusively from home, and 24.8% had a hybrid arrangement. Most participants were employees (60.4%), female (65.7%), single (60.4%), and university educated (93.5%). The majority lived in Beirut or Mount Lebanon (73.9%) and reported moderate-to-high income (80.5%). The mean age was 30.55 ± 10.80 years, the mean household crowding index was 1.08 ± 0.54, the mean number of children was 0.98 ± 1.33, and the mean financial well-being score was 36.90 ± 16.73.

Table 2 Sociodemographic characteristic of the participants (N = 230).
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Construct validity: factor analysis

Table 3 shows the exploratory factor analysis of the Perception of Telework Practices (PTP) scale. For the PTP total scale, the Varimax-rotated matrix produced two factors with eigenvalues > 1, explaining 53.34% of the variance ( KMO = 0.925; Bartlett’s test of sphericity p < 0.001; Cronbach’s alpha = 0.942). The Varimax solution supports a two-subscale structure—perceived advantages and perceived drawbacks.

Table 3 Factor analysis of the telework perception scales.
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For the perceived advantages subscale, the Promax rotated matrix produced two factors with eigenvalues > 1, explaining 65.25% of the variance (KMO = 0.906; Bartlett’s test of sphericity p < 0.001; Cronbach’s alpha = 0.916). These components correspond to (1) increased flexibility and cost savings and (2) enhanced productivity and work/life balance.

For the perceived drawbacks subscale, the Promax rotated matrix produced three factors with eigenvalues > 1, explaining 62.67% of the variance (KMO = 0.943; Bartlett’s test of sphericity p < 0.001; Cronbach’s alpha = 0.954). The factors correspond to (1) telework overall challenges, (2) decreased productivity, and (3) telework lifestyle impact.

The scree plots for the Perception of Telework Practices (PTP) scale and its subscales display the eigenvalues of extracted factors (Kaiser criterion, eigenvalues > 1). As shown in Fig. 1, a distinct elbow appears after the second factor for both the PTP total scale and the Perceived Advantages of Telework subscale (PATS), supporting a two-factor solution. For the Perceived Drawbacks subscale (PDTS), the elbow occurs after the third factor, supporting a three-factor solution.

Fig. 1
Fig. 1
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Scree Plot of Eigenvalues for the Perception of Telework Practices scales.

Confirmatory Factor Analysis (CFA) was conducted on a randomly selected half of the sample to validate the factor structure of the scales used in the exploratory factor analysis (EFA). For the PTP total scale, fit indices were χ2/df = 2.56, CFI = 0.730, TLI = 0.712, and RMSEA = 0.116 (95% CI [0.108–0.123]. For the PATS, the model yielded χ2/df ratio of = 3.18, CFI = 0.868, TLI = 0.836, and RMSEA = 0.137 (95% CI [0.114–0.160]). For the PTDS, the model yielded χ2/df ratio of = 2.29, CFI = 0.864, TLI = 0.847, and RMSEA = 0.105 (95% CI [0.093–0.118]). Results are presented in Table 4.

Table 4 Confirmatory factor analysis conducted on a random half-subsample.
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Description of the scales

Table 5 summarizes the descriptive statistics (median, mean, SD, and range) for all study scales. For the PTP total scale, the mean was 113.20 ± 22.95 and the median was 119.00 [min 36; max 161]. For the PATS, the median was 41.00 [min 12; max 60] and the mean was 40.22 ± 9.62. For the PTDS, the median was 77 [min 24; max 110] and the mean was 72.98 ± 18.43. Regarding the E-Work Life Scale, the mean was 46.78 ± 16.75, and the median was 51.00 [min 0; max 84]. Overall, awareness of telework’s advantages and drawbacks was relatively high (70%), whereas satisfaction with telework on the EWL was moderate, reaching only 56%.

Table 5 Description of telework-related scales in the study.
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Structural validity: correlation analysis

Pearson correlations showed that PTP, PATS, and PDTS total scores were positively intercorrelated and each correlated positively with their constituent factors (all p < 0.05). Within PATS, the total score correlated very strongly with Factor 1 (r = 0.906, p < 0.001) and Factor 2 (r = 0.904, p < 0.001); the two factors were strongly intercorrelated (r = 0.638, p < 0.001). The PTP total score was moderately correlated with PATS Factor 2 (r = 0.444, p < 0.001). Within PDTS, the total score correlated very strongly with Factor 1 (r = 0.952, p < 0.001), Factor 2 (r = 0.902, p < 0.001), and Factor 3 (r = 0.870, p < 0.001). Strong correlations were also observed among PDTS factors: F1–F2 (r = 0.794), F1–F3 (r = 0.736), and F2–F3 (r = 0.703) (all p < 0.001; Table 6).

Table 6 Pearson correlation analysis between the Advantages/ drawbacks of telework subscales and their own factors.
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Bivariate analysis

No significant differences by work status were observed for PTP, PATS, or PDTS (all p > 0.05). Mean PTP scores were highest among hybrid workers (115.21 ± 19.57), followed by on-site workers (112.65 ± 24.14) and those working from home (112.27 ± 23.78; p = 0.748). For PATS, means were 40.71 ± 10.57 (hybrid), 40.19 ± 10.37 (work-from-home), and 40.00 ± 8.93 (on-site; p = 0.899). For PDTS, means were 74.49 ± 15.60 (hybrid), 72.08 ± 18.95 (work-from-home), and 72.64 ± 19.49 (on-site; p = 0.767) (Fig. 2).

Fig. 2
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Associations Between Perception of Telework Practices, Telework Advantages/Drawbacks and Working Status.

Pearson correlations indicated that PTP, PATS, and PDTS total scores were positively intercorrelated and each correlated positively with their constituent factors (all p < 0.05). The strongest association with PTP was PDTS (r = 0.915, p < 0.001), followed by PATS (r = 0.633, p < 0.001), as expected given their contribution to the total score. PTP also showed weak but significant correlations with the EWL total and its subscales (r = 0.206–0.304), suggesting that EWL captures related but distinct aspects of the e-work experience (Table 7).

Table 7 Bivariate analysis taking the advantages and drawbacks of telework as the dependent variables.
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When PATS was the focus, a moderate positive correlation emerged with EWL–Productivity (r = 0.444, p < 0.001), indicating that perceiving more advantages of telework is associated with higher self-reported productivity. Additional weak but significant correlations were observed with the EWL total (r = 0.336, p < 0.001), EWL–Flexibility (r = 0.297, p < 0.001), and EWL–Work–Life Interference (r = 0.244, p < 0.001). A very weak correlation with EWL–Organizational Trust (r = 0.183, p = 0.005) was also noted. PATS and PDTS were weakly but significantly correlated (r = 0.266, p < 0.001), indicating that respondents can recognize both benefits and challenges concurrently.

For PDTS, weak but significant correlations were found with the EWL total (r = 0.203, p < 0.001) and EWL–Work–Life Interference (r = 0.246, p < 0.001), and a very weak correlation with EWL–Organizational Trust (r = 0.167, p = 0.011). PDTS was not significantly correlated with EWL–Productivity (r = 0.107, p = 0.104) or EWL–Flexibility (r = 0.102, p = 0.123) (Table 7).

Discussion

This study successfully validated the Perception of the Telework Practices (PTP) scale among 230 Lebanese workers from diverse backgrounds, comprising two robust subscales: the Perceived Advantages of Telework Subscale (PATS) and the Perceived Drawbacks of Telework Subscale (PDTS). The validation results demonstrate that this instrument effectively captures Lebanese workers’ perceptions of telework within their unique socioeconomic context, providing a reliable tool for businesses, individuals, and managers to assist teleworkers in creating well-being management plans.

The developed scale demonstrated excellent psychometric properties with high construct validity (KMO = 0.925 for the total scale, 0.906–0.943 for subscales), structural validity (evidenced by strong correlations between subscales and factors), and reliability (Cronbach’s alpha = 0.942 for the total scale, 0.916–0.954 for subscales). These robust psychometric indicators align with and exceed benchmarks established by comparable international studies. The telework perception scale (Tele-Cov-19) for Peruvian schoolteachers demonstrated good content-based validity, internal structure, and reliability49, while the Remote Working Benefits & Disadvantages scale showed good construct validity, confirmatory indices, reliability indices, and convergent and discriminant validity40. The E-Work Life scale was created to measure remote e-working29, and other studies have evaluated perception aspects of telework advantages and disadvantages50,51,52. However, existing instruments either focus on narrow populations (teachers), limited dimensions (satisfaction only), or were developed in stable economic contexts that cannot capture infrastructure-related challenges. The PTP scale’s comprehensive approach—integrating personal, professional, social, and environmental dimensions within a resource-constrained context—establishes its unique utility for exploring telework perceptions in developing country populations.

The PTP scale and subscales include items addressing personal, professional, social, and environmental aspects specific to Lebanon’s multi-crisis context, aligning with global studies across various worker populations13,53,54,55. The inclusion of electricity outages and unstable internet connection items—rarely or not cited in other studies—directly addresses infrastructure challenges prevalent in Lebanon’s current economic crisis36,56. The high cost of improving these services makes them inaccessible to substantial population segments, a reality captured in the PTP scale’s factor structure and reflected in participants’ responses.

This study revealed a significant perception-satisfaction disparity that provides crucial insights into Lebanese telework experiences. While participants demonstrated solid awareness of teleworking advantages and drawbacks (67%), satisfaction levels reached only 56%—notably lower than European and Brazilian studies53,54. This finding suggests Lebanese participants experienced more negative telework conditions compared to their international counterparts, with infrastructure limitations providing a plausible explanation directly supported by PTP’s Lebanon-specific items. Another potential factor could be the voluntariness of working remotely, as described in a study conducted before and after the COVID-19 pandemic57, revealing that pre-pandemic participants, who were more likely to choose remote work voluntarily, reported fewer disadvantages the more they engaged in telework. However, this pattern was not the same for employees during COVID-19, supporting our interpretation that crisis-driven, involuntary telework adoption in Lebanon—compounded by infrastructure limitations—created particularly challenging conditions reflected in our 56% satisfaction rate.

The low but significant correlation between advantage and drawback scales reveals that few participants simultaneously agreed on both positive and negative aspects, indicating nuanced perceptions shaped by contextual realities. The convergent validity analysis with telework satisfaction (EWL) demonstrates that participants with positive telework perceptions (high PATS scores) exhibited satisfaction across all EWL dimensions—work-life balance, productivity, flexibility, and organizational trust. Conversely, those with negative perceptions (high PDTS scores) specifically devalued productivity and flexibility aspects, directly linking to reported disadvantages, including personal health issues, professional inability to conduct work properly, environmental inappropriateness, and social communication barriers. These patterns echo European findings54, which emphasized work-life balance, improved work efficiency, and greater work control as advantages, while disadvantages included home office constraints, work uncertainties, and inadequate tools. However, the Lebanese data reveal infrastructure challenges as fundamental moderators of these relationships.

Our findings directly inform understanding of Lebanese institutional responses to telework. Despite global telework trends58 and the lack of clear regulations59, the uncertainty of many Lebanese institutions about teleworker productivity in current conditions led to the imposition of physical presence after the lifting of lockdown. This response, as our data suggests, may reflect legitimate concerns related to productivity and infrastructure rather than mere organizational resistance.

For Lebanese institutions and employers, our findings indicate that addressing infrastructure support is a prerequisite to successful telework implementation. The demonstrated impact of infrastructure adequacy on our participants’ productivity and flexibility perceptions suggests that organizational telework policies must account for technological limitations that fundamentally alter the telework experience compared to resource-rich environments.

For Lebanese policymakers, our validation provides empirical evidence supporting infrastructure investment priorities. Given our finding that electricity outages and connectivity issues directly impact telework satisfaction, government encouragement of necessary infrastructure and skills investments becomes critical for optimizing telework benefits in terms of workers’ productivity and well-being, as demonstrated by telework’s established productivity improvements60 extending beyond pandemic constraints.

For Lebanese researchers, our validated scale provides a culturally appropriate instrument for investigating telework dynamics within Middle Eastern contexts, addressing the limitations of instruments developed in politically and economically stable environments that cannot capture local infrastructure and cultural realities.

Implications of the study

This cross-sectional study of 230 Lebanese workers developed and validated standardized scales that capture perceived benefits and drawbacks of telework, helping to address the current shortage of robust measurement tools. Grounded in Lebanon’s economic, cultural, and infrastructure realities yet adaptable for international use, the instrument enables policymakers to refine labor provisions on remote work and to prioritize connectivity investments because employee experience is now quantified. Employers can audit perceptions, identify pain points, and tailor hybrid policies, workload planning, management practices, and IT/ergonomic support, while tracking changes over time to monitor productivity, job satisfaction, and well-being. Researchers can examine links between telework and organizational effectiveness and generate evidence-based recommendations; educators and students can use the scales to interrogate advantages (e.g., flexibility, cost savings) and drawbacks (e.g., communication barriers, isolation). Employees can draw on the findings to articulate needs, negotiate workable arrangements, and inform career decisions, and practitioners can design targeted support programs and training that maximize benefits and mitigate drawbacks in the Lebanese context.

Limitations of the study

Despite the advantages identified, this validation study lacks several procedures essential for confirming the validity and reliability of the scales. It is thus recommended to conduct a confirmatory factor analysis on a different sample of teleworkers. A small sample size was selected in this study, with the majority of participants having a university education level, which might decrease the generalizability of the results to broader populations. The education characteristics probably represent the group of people who use telework the most frequently. A larger sample size is generally required to ensure robust factor analysis and the generalizability of the results. Expanding the sample size is a top priority for future studies to fully validate the instrument. Although a CFA was conducted on a randomly selected 50% subsample to support the results of the EFA, the overall sample size was relatively small, and the fit indices were only partially satisfactory. A future analytical study with a distinct and sufficiently large sample, including CFA, will be necessary for a more robust and comprehensive validation of the scale. The snowball sampling technique used in this study is a non-random sampling method, which may lead to the selection of participants sharing similar characteristics (young, female, university-educated individuals). This could introduce selection bias and limit the representativeness of the sample, affecting the generalizability of the findings. In addition, selecting individuals with remote work experience or hybrid work experience is recommended to assess the pros and cons of remote work. Furthermore, concerning the rigor of scale construction, the number of participants is preferred to be over three hundred valid questionnaires, as in the literature, the factor analysis requires 5–10 times the number of items. Also, the sample was not representative of all remote workers, as the majority were women with a university education level. The choice of remote video software was not taken into consideration, which might affect job satisfaction. Assessing test–retest, inter-rater, and intra-rater reliability would further strengthen the reliability analysis. Lastly, expanding the sample to include older individuals is also advised, given the predominantly young age of the studied population.

Conclusion

This study successfully developed and validated the Perception of Telework Practices (PTP) scale with excellent psychometric properties: construct validity (KMO = 0.925–0.943), reliability (Cronbach’s alpha = 0.916–0.954), and robust factor structures explaining 53–65% of variance. The gap between high telework awareness (70%) and lower satisfaction (56%) indicates contextual challenges in resource-constrained environments. Priority research directions include confirmatory factor analysis on larger samples, cross-cultural validation, and longitudinal assessment.

The scale validated in this study provides a reliable tool for measuring telework perceptions in developing country contexts, supporting evidence-based policy and organizational decisions in modern workplaces. Cross-cultural implementation will require adapting context-specific items while preserving the validated factor structure, particularly considering infrastructure variations that fundamentally shape telework experiences in different settings.